Load libraries

library(knitr)
library(rmdformats)
library(ggplot2)
library(ggpubr)
library(GGally)
library(car)
library(tidyverse)
library(lme4)
library(lmerTest)
library("MuMIn")
library(lmtest)
library(boot)

Read dataset

AllSubs_NeuralActivation <- read.csv('/Users/luisalvarez/Documents/GitHub/RM_Thesis_Neuroforecasting/ProcessedData/AllSubs_NeuralActivation_Aggregate_Combined_Comedy_clean.csv')

Create data frames for each model.

# Define aggregate variables. 
All_Gross_W1_log <- log(AllSubs_NeuralActivation$Gross_US_W1_num)
All_Theaters_W1 <- AllSubs_NeuralActivation$Theaters_US_W1_num

All_Gross_M1_log <- log(AllSubs_NeuralActivation$Gross_US_M1)
All_Theaters_M1 <- AllSubs_NeuralActivation$Theaters_US_M1

# Define affect variables.
All_PA <- AllSubs_NeuralActivation$Pos_arousal_scaled
All_NA <- AllSubs_NeuralActivation$Neg_arousal_scaled

FW_US_M1_df <- data.frame(All_Gross_W1_log, All_Theaters_W1) 
FM_US_M14_df <- data.frame(All_Gross_M1_log, All_Theaters_M1) 
# Define ISC variables. 
All_NAcc_ISC <- AllSubs_NeuralActivation$NAcc_ISC
All_AIns_ISC <- AllSubs_NeuralActivation$AIns_ISC
All_MPFC_ISC <- AllSubs_NeuralActivation$MPFC_ISC

# Define models. 
FW_US_M2_df <- data.frame(All_NAcc_ISC, All_AIns_ISC, All_MPFC_ISC) 
FW_US_M3_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_ISC, All_AIns_ISC, All_MPFC_ISC) 
FM_US_M16_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_ISC, All_AIns_ISC, All_MPFC_ISC) 
# Define whole variables. 
All_NAcc_whole <- AllSubs_NeuralActivation$NAcc_whole
All_AIns_whole <- AllSubs_NeuralActivation$AIns_whole
All_MPFC_whole <- AllSubs_NeuralActivation$MPFC_whole

# Define models. 
FW_US_M4_df <- data.frame(All_NAcc_whole, All_AIns_whole, All_MPFC_whole) 
FW_US_M5_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_whole, All_AIns_whole, All_MPFC_whole)
FM_US_M18_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_whole, All_AIns_whole, All_MPFC_whole)
# Define onset variables. 
All_NAcc_onset <- AllSubs_NeuralActivation$NAcc_onset
All_AIns_onset <- AllSubs_NeuralActivation$AIns_onset
All_MPFC_onset <- AllSubs_NeuralActivation$MPFC_onset

# Define models. 
FW_US_M6_df <- data.frame(All_NAcc_onset, All_AIns_onset, All_MPFC_onset) 
FW_US_M7_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_onset, All_MPFC_onset)
FM_US_M20_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_onset, All_MPFC_onset)
# Define middle variables. 
All_NAcc_middle <- AllSubs_NeuralActivation$NAcc_middle
All_AIns_middle <- AllSubs_NeuralActivation$AIns_middle
All_MPFC_middle <- AllSubs_NeuralActivation$MPFC_middle

# Define models. 
FW_US_M8_df <- data.frame(All_NAcc_middle, All_AIns_middle, All_MPFC_middle) 
FW_US_M9_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_middle, All_AIns_middle, All_MPFC_middle) 
FM_US_M22_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_middle, All_AIns_middle, All_MPFC_middle)
# Define offset variables. 
All_NAcc_offset <- AllSubs_NeuralActivation$NAcc_offset
All_AIns_offset <- AllSubs_NeuralActivation$AIns_offset
All_MPFC_offset <- AllSubs_NeuralActivation$MPFC_offset

# Define models. 
FW_US_M10_df <- data.frame(All_NAcc_offset, All_AIns_offset, All_MPFC_offset) 
FW_US_M11_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_offset, All_AIns_offset, All_MPFC_offset)
FM_US_M24_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_offset, All_AIns_offset, All_MPFC_offset)

# Seq models. 
FW_US_M12_df <- data.frame(All_NAcc_onset, All_AIns_middle, All_MPFC_offset) 
FW_US_M13_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_middle, All_MPFC_offset)
FM_US_M26_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_middle, All_MPFC_offset)

Neuroforecasting: First Week US.

M1: Behavioral data + Affective data


Call:
lm(formula = log(Gross_US_W1_num) ~ Theaters_US_W1_num + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.21830 -0.37441  0.02446  0.39529  1.19424 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)               12.4675794  0.4474662  27.863 2.83e-12 ***
Theaters_US_W1_num         0.0011595  0.0001464   7.919 4.17e-06 ***
scale(Pos_arousal_scaled) -0.0631872  0.1922402  -0.329    0.748    
scale(Neg_arousal_scaled)  0.2691857  0.1889371   1.425    0.180    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.7255 on 12 degrees of freedom
Multiple R-squared:  0.8442,    Adjusted R-squared:  0.8052 
F-statistic: 21.67 on 3 and 12 DF,  p-value: 3.905e-05

           R2m       R2c
[1,] 0.8125419 0.8125419
[1] 40.53391

FW_US_M2: ISC data alone


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(NAcc_ISC) + 
    scale(AIns_ISC) + scale(MPFC_ISC), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.38292 -0.39035  0.00291  0.42719  1.30755 

Coefficients:
                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)        12.4615011  0.4879555  25.538 3.83e-11 ***
Theaters_US_W1_num  0.0011617  0.0001602   7.250 1.64e-05 ***
scale(NAcc_ISC)     0.1735213  0.2448084   0.709    0.493    
scale(AIns_ISC)    -0.0210687  0.2575483  -0.082    0.936    
scale(MPFC_ISC)    -0.2471274  0.2289210  -1.080    0.303    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.7769 on 11 degrees of freedom
Multiple R-squared:  0.8362,    Adjusted R-squared:  0.7766 
F-statistic: 14.04 on 4 and 11 DF,  p-value: 0.0002672

           R2m       R2c
[1,] 0.7891992 0.7891992
[1] 43.33375

FW_US_M3: ISC data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_ISC) + scale(AIns_ISC) + 
    scale(MPFC_ISC), data = AllSubs_NeuralActivation)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.9034 -0.2448 -0.1094  0.2894  0.8893 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)               12.2654495  0.3976897  30.842 1.94e-10 ***
Theaters_US_W1_num         0.0012319  0.0001317   9.353 6.23e-06 ***
scale(Pos_arousal_scaled) -0.2113917  0.2221020  -0.952   0.3661    
scale(Neg_arousal_scaled)  0.5028299  0.1826932   2.752   0.0224 *  
scale(NAcc_ISC)            0.4828712  0.2569446   1.879   0.0929 .  
scale(AIns_ISC)           -0.0425640  0.2477111  -0.172   0.8674    
scale(MPFC_ISC)           -0.4886649  0.2047304  -2.387   0.0408 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.6035 on 9 degrees of freedom
Multiple R-squared:  0.9191,    Adjusted R-squared:  0.8652 
F-statistic: 17.05 on 6 and 9 DF,  p-value: 0.0001896

           R2m       R2c
[1,] 0.8721157 0.8721157
[1] 36.04087

FW_US_M4: Whole data alone


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(NAcc_whole) + 
    scale(AIns_whole) + scale(MPFC_whole), data = AllSubs_NeuralActivation)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.2756 -0.4046  0.2554  0.3573  0.8457 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)        1.263e+01  4.182e-01  30.189 6.23e-12 ***
Theaters_US_W1_num 1.103e-03  1.366e-04   8.072 6.00e-06 ***
scale(NAcc_whole)  1.049e-01  1.960e-01   0.535   0.6030    
scale(AIns_whole)  6.497e-02  1.907e-01   0.341   0.7397    
scale(MPFC_whole)  3.494e-01  1.834e-01   1.906   0.0832 .  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.6833 on 11 degrees of freedom
Multiple R-squared:  0.8733,    Adjusted R-squared:  0.8272 
F-statistic: 18.96 on 4 and 11 DF,  p-value: 6.743e-05

           R2m       R2c
[1,] 0.8348434 0.8348434
[1] 39.22441

FW_US_M5: Whole data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_whole) + scale(AIns_whole) + 
    scale(MPFC_whole), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.72409 -0.20077  0.05612  0.32143  0.56474 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)               12.5236381  0.3368316  37.181 3.65e-11 ***
Theaters_US_W1_num         0.0011395  0.0001108  10.285 2.83e-06 ***
scale(Pos_arousal_scaled) -0.0240594  0.1541740  -0.156   0.8794    
scale(Neg_arousal_scaled)  0.5143768  0.1705727   3.016   0.0146 *  
scale(NAcc_whole)          0.3995877  0.1855911   2.153   0.0597 .  
scale(AIns_whole)         -0.1882468  0.1704791  -1.104   0.2981    
scale(MPFC_whole)          0.3402472  0.1519678   2.239   0.0519 .  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.5317 on 9 degrees of freedom
Multiple R-squared:  0.9372,    Adjusted R-squared:  0.8954 
F-statistic:  22.4 on 6 and 9 DF,  p-value: 6.255e-05

           R2m       R2c
[1,] 0.8995921 0.8995921
[1] 31.98644

FW_US_M6: Onset data alone


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(NAcc_onset) + 
    scale(AIns_onset) + scale(MPFC_onset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.58549 -0.31399  0.00325  0.30015  1.33657 

Coefficients:
                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)        12.5939630  0.5219388  24.129 7.08e-11 ***
Theaters_US_W1_num  0.0011143  0.0001729   6.443 4.79e-05 ***
scale(NAcc_onset)  -0.0383730  0.2490668  -0.154    0.880    
scale(AIns_onset)  -0.2714296  0.3475997  -0.781    0.451    
scale(MPFC_onset)   0.1635024  0.3274233   0.499    0.627    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.7902 on 11 degrees of freedom
Multiple R-squared:  0.8306,    Adjusted R-squared:  0.7689 
F-statistic: 13.48 on 4 and 11 DF,  p-value: 0.0003201

          R2m      R2c
[1,] 0.782359 0.782359
[1] 43.87564

FW_US_M7: Onset data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_onset) + scale(AIns_onset) + 
    scale(MPFC_onset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.00596 -0.42891  0.06107  0.33857  1.20079 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)               12.5037757  0.5296610  23.607 2.09e-09 ***
Theaters_US_W1_num         0.0011466  0.0001757   6.525 0.000108 ***
scale(Pos_arousal_scaled) -0.1620195  0.2546050  -0.636 0.540388    
scale(Neg_arousal_scaled)  0.3003505  0.2375941   1.264 0.237939    
scale(NAcc_onset)          0.2130005  0.3290135   0.647 0.533542    
scale(AIns_onset)         -0.3247931  0.3756072  -0.865 0.409651    
scale(MPFC_onset)          0.0908062  0.3453251   0.263 0.798503    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.7955 on 9 degrees of freedom
Multiple R-squared:  0.8595,    Adjusted R-squared:  0.7658 
F-statistic: 9.176 on 6 and 9 DF,  p-value: 0.002047

           R2m       R2c
[1,] 0.7858827 0.7858827
[1] 44.87972

FW_US_M8: Middle data alone


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(NAcc_middle) + 
    scale(AIns_middle) + scale(MPFC_middle), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.28065 -0.08859  0.02742  0.45957  0.71604 

Coefficients:
                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)        12.5103123  0.4667586  26.803 2.27e-11 ***
Theaters_US_W1_num  0.0011442  0.0001542   7.419 1.33e-05 ***
scale(NAcc_middle)  0.3449983  0.2323279   1.485    0.166    
scale(AIns_middle)  0.1234687  0.2221701   0.556    0.590    
scale(MPFC_middle) -0.1757236  0.2192511  -0.801    0.440    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.7179 on 11 degrees of freedom
Multiple R-squared:  0.8601,    Adjusted R-squared:  0.8093 
F-statistic: 16.91 on 4 and 11 DF,  p-value: 0.0001147

           R2m       R2c
[1,] 0.8184974 0.8184974
[1] 40.80755

FW_US_M9: Middle data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_middle) + scale(AIns_middle) + 
    scale(MPFC_middle), data = AllSubs_NeuralActivation)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.0602 -0.2823  0.1308  0.3278  0.7616 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)               12.4515030  0.4946438  25.173 1.18e-09 ***
Theaters_US_W1_num         0.0011653  0.0001639   7.109 5.61e-05 ***
scale(Pos_arousal_scaled) -0.1373489  0.2486434  -0.552    0.594    
scale(Neg_arousal_scaled)  0.1460506  0.2456896   0.594    0.567    
scale(NAcc_middle)         0.2993163  0.2459860   1.217    0.255    
scale(AIns_middle)         0.1336529  0.3170095   0.422    0.683    
scale(MPFC_middle)        -0.1413418  0.2571878  -0.550    0.596    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.7481 on 9 degrees of freedom
Multiple R-squared:  0.8758,    Adjusted R-squared:  0.7929 
F-statistic: 10.57 on 6 and 9 DF,  p-value: 0.001212

           R2m       R2c
[1,] 0.8087687 0.8087687
[1] 42.91168

FW_US_M10: Offset data alone


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(NAcc_offset) + 
    scale(AIns_offset) + scale(MPFC_offset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.81940 -0.37776  0.01451  0.25168  0.86566 

Coefficients:
                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)        12.3517604  0.3624849  34.075 1.67e-12 ***
Theaters_US_W1_num  0.0012010  0.0001193  10.070 6.89e-07 ***
scale(NAcc_offset) -0.1513350  0.1916306  -0.790   0.4464    
scale(AIns_offset)  0.1405807  0.1655208   0.849   0.4138    
scale(MPFC_offset)  0.5445114  0.1878277   2.899   0.0145 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.5712 on 11 degrees of freedom
Multiple R-squared:  0.9115,    Adjusted R-squared:  0.8793 
F-statistic: 28.31 on 4 and 11 DF,  p-value: 9.732e-06

           R2m       R2c
[1,] 0.8830375 0.8830375
[1] 33.4901

FW_US_M11: Onset data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_offset) + scale(AIns_offset) + 
    scale(MPFC_offset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.77884 -0.18659  0.05761  0.19377  0.57414 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)                1.241e+01  2.958e-01  41.941 1.24e-11 ***
Theaters_US_W1_num         1.182e-03  9.747e-05  12.126 7.05e-07 ***
scale(Pos_arousal_scaled)  1.547e-01  1.331e-01   1.162  0.27513    
scale(Neg_arousal_scaled)  3.532e-01  1.307e-01   2.702  0.02433 *  
scale(NAcc_offset)        -5.731e-02  1.588e-01  -0.361  0.72646    
scale(AIns_offset)         1.586e-02  1.425e-01   0.111  0.91384    
scale(MPFC_offset)         6.169e-01  1.570e-01   3.928  0.00347 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4622 on 9 degrees of freedom
Multiple R-squared:  0.9526,    Adjusted R-squared:  0.921 
F-statistic: 30.13 on 6 and 9 DF,  p-value: 1.819e-05

           R2m       R2c
[1,] 0.9233876 0.9233876
[1] 27.50086

FW_US_M12: Seq data alone


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(NAcc_onset) + 
    scale(AIns_middle) + scale(MPFC_offset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.96161 -0.26052  0.04203  0.26418  0.85995 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)        1.256e+01  3.457e-01  36.343 8.24e-13 ***
Theaters_US_W1_num 1.125e-03  1.138e-04   9.890 8.26e-07 ***
scale(NAcc_onset)  7.063e-02  1.534e-01   0.460  0.65417    
scale(AIns_middle) 2.174e-01  1.467e-01   1.482  0.16644    
scale(MPFC_offset) 5.133e-01  1.526e-01   3.363  0.00633 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.544 on 11 degrees of freedom
Multiple R-squared:  0.9197,    Adjusted R-squared:  0.8905 
F-statistic: 31.49 on 4 and 11 DF,  p-value: 5.737e-06

           R2m       R2c
[1,] 0.8935894 0.8935894
[1] 31.93091

FW_US_M13: Seq data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_W1_num) ~ +Theaters_US_W1_num + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_onset) + scale(AIns_middle) + 
    scale(MPFC_offset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.55141 -0.11755 -0.01153  0.16097  0.56232 

Coefficients:
                           Estimate Std. Error t value Pr(>|t|)    
(Intercept)               1.243e+01  2.378e-01  52.247 1.73e-12 ***
Theaters_US_W1_num        1.174e-03  7.844e-05  14.973 1.15e-07 ***
scale(Pos_arousal_scaled) 7.111e-02  1.327e-01   0.536 0.605076    
scale(Neg_arousal_scaled) 4.784e-01  1.250e-01   3.827 0.004043 ** 
scale(NAcc_onset)         2.905e-01  1.268e-01   2.292 0.047642 *  
scale(AIns_middle)        9.200e-03  1.297e-01   0.071 0.945004    
scale(MPFC_offset)        6.808e-01  1.170e-01   5.817 0.000254 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.3699 on 9 degrees of freedom
Multiple R-squared:  0.9696,    Adjusted R-squared:  0.9494 
F-statistic: 47.89 on 6 and 9 DF,  p-value: 2.521e-06

           R2m       R2c
[1,] 0.9503822 0.9503822
[1] 20.37305

Neuroforecasting: First Month US.

FM_US_M14: Behavioral data + affective data


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled), data = AllSubs_NeuralActivation)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.4772 -0.2704 -0.1041  0.2875  0.6834 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)               15.1927135  0.2659405  57.128 5.46e-16 ***
Theaters_US_M1             0.0001917  0.0000259   7.401 8.26e-06 ***
scale(Pos_arousal_scaled)  0.1061626  0.1077262   0.985    0.344    
scale(Neg_arousal_scaled) -0.1161456  0.1040014  -1.117    0.286    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.3954 on 12 degrees of freedom
Multiple R-squared:  0.8588,    Adjusted R-squared:  0.8235 
F-statistic: 24.33 on 3 and 12 DF,  p-value: 2.18e-05

           R2m       R2c
[1,] 0.8294972 0.8294972
[1] 21.10915

FM_US_M15: ISC data alone


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(NAcc_ISC) + 
    scale(AIns_ISC) + scale(MPFC_ISC), data = AllSubs_NeuralActivation)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.4831 -0.2525 -0.1129  0.2019  0.8080 

Coefficients:
                  Estimate Std. Error t value Pr(>|t|)    
(Intercept)      1.499e+01  2.894e-01  51.799 1.71e-14 ***
Theaters_US_M1   2.131e-04  2.824e-05   7.548 1.13e-05 ***
scale(NAcc_ISC)  1.574e-01  1.362e-01   1.155    0.272    
scale(AIns_ISC) -1.157e-01  1.406e-01  -0.823    0.428    
scale(MPFC_ISC) -3.612e-02  1.292e-01  -0.280    0.785    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.425 on 11 degrees of freedom
Multiple R-squared:  0.8504,    Adjusted R-squared:  0.796 
F-statistic: 15.63 on 4 and 11 DF,  p-value: 0.0001645

           R2m       R2c
[1,] 0.8065301 0.8065301
[1] 24.03129

FM_US_M16: ISC data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_ISC) + scale(AIns_ISC) + 
    scale(MPFC_ISC), data = AllSubs_NeuralActivation)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.4909 -0.2308 -0.1194  0.3020  0.6478 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)                1.513e+01  3.792e-01  39.891 1.95e-11 ***
Theaters_US_M1             1.985e-04  3.802e-05   5.221 0.000549 ***
scale(Pos_arousal_scaled)  4.136e-02  1.877e-01   0.220 0.830562    
scale(Neg_arousal_scaled) -1.348e-01  1.430e-01  -0.942 0.370562    
scale(NAcc_ISC)            7.412e-02  2.233e-01   0.332 0.747526    
scale(AIns_ISC)           -1.100e-01  1.929e-01  -0.570 0.582576    
scale(MPFC_ISC)            4.567e-02  1.614e-01   0.283 0.783648    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4477 on 9 degrees of freedom
Multiple R-squared:  0.8642,    Adjusted R-squared:  0.7736 
F-statistic: 9.544 on 6 and 9 DF,  p-value: 0.001772

           R2m       R2c
[1,] 0.7924233 0.7924233
[1] 26.486

FM_US_M17: Whole data alone


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(NAcc_whole) + 
    scale(AIns_whole) + scale(MPFC_whole), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.48416 -0.25762 -0.05023  0.17241  0.66448 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)        1.508e+01  2.883e-01  52.323 1.53e-14 ***
Theaters_US_M1     2.031e-04  2.808e-05   7.230 1.69e-05 ***
scale(NAcc_whole)  8.483e-02  1.265e-01   0.671    0.516    
scale(AIns_whole)  6.667e-02  1.261e-01   0.529    0.607    
scale(MPFC_whole) -1.177e-02  1.142e-01  -0.103    0.920    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4282 on 11 degrees of freedom
Multiple R-squared:  0.8481,    Adjusted R-squared:  0.7929 
F-statistic: 15.36 on 4 and 11 DF,  p-value: 0.0001783

           R2m       R2c
[1,] 0.8037433 0.8037433
[1] 24.27266

FM_US_M18: Whole data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_whole) + scale(AIns_whole) + 
    scale(MPFC_whole), data = AllSubs_NeuralActivation)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.4385 -0.2695 -0.0189  0.2233  0.5891 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)                1.544e+01  3.333e-01  46.326 5.09e-12 ***
Theaters_US_M1             1.656e-04  3.334e-05   4.966 0.000774 ***
scale(Pos_arousal_scaled)  1.405e-01  1.251e-01   1.123 0.290457    
scale(Neg_arousal_scaled) -2.440e-01  1.479e-01  -1.649 0.133464    
scale(NAcc_whole)         -1.344e-01  1.674e-01  -0.803 0.442646    
scale(AIns_whole)          2.397e-01  1.535e-01   1.561 0.152892    
scale(MPFC_whole)          4.299e-02  1.158e-01   0.371 0.719043    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4024 on 9 degrees of freedom
Multiple R-squared:  0.8903,    Adjusted R-squared:  0.8172 
F-statistic: 12.17 on 6 and 9 DF,  p-value: 0.0007106

           R2m       R2c
[1,] 0.8296253 0.8296253
[1] 23.06842

FM_US_M19: Onset data alone


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(NAcc_onset) + 
    scale(AIns_onset) + scale(MPFC_onset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.43418 -0.31495 -0.04144  0.25868  0.66861 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)        1.509e+01  3.108e-01  48.566 3.46e-14 ***
Theaters_US_M1     2.020e-04  3.077e-05   6.564 4.06e-05 ***
scale(NAcc_onset)  1.604e-01  1.328e-01   1.208    0.252    
scale(AIns_onset)  2.949e-02  1.747e-01   0.169    0.869    
scale(MPFC_onset) -1.160e-01  1.717e-01  -0.676    0.513    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4117 on 11 degrees of freedom
Multiple R-squared:  0.8596,    Adjusted R-squared:  0.8086 
F-statistic: 16.84 on 4 and 11 DF,  p-value: 0.0001171

           R2m       R2c
[1,] 0.8178498 0.8178498
[1] 23.01581

FM_US_M20: Onset data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_onset) + scale(AIns_onset) + 
    scale(MPFC_onset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.46535 -0.28851 -0.09242  0.27231  0.55967 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)                1.516e+01  3.447e-01  43.975 8.12e-12 ***
Theaters_US_M1             1.954e-04  3.425e-05   5.703 0.000293 ***
scale(Pos_arousal_scaled)  8.363e-02  1.440e-01   0.581 0.575569    
scale(Neg_arousal_scaled) -6.981e-02  1.338e-01  -0.522 0.614409    
scale(NAcc_onset)          7.689e-02  1.829e-01   0.420 0.683984    
scale(AIns_onset)          6.685e-02  2.022e-01   0.331 0.748547    
scale(MPFC_onset)         -1.022e-01  1.934e-01  -0.529 0.609896    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4422 on 9 degrees of freedom
Multiple R-squared:  0.8675,    Adjusted R-squared:  0.7792 
F-statistic: 9.823 on 6 and 9 DF,  p-value: 0.001594

           R2m       R2c
[1,] 0.7971308 0.7971308
[1] 26.08615

FM_US_M17: Middle data alone


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(NAcc_middle) + 
    scale(AIns_middle) + scale(MPFC_middle), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.55081 -0.27048 -0.06784  0.26948  0.60581 

Coefficients:
                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)         1.529e+01  3.277e-01  46.660 5.36e-14 ***
Theaters_US_M1      1.813e-04  3.257e-05   5.568 0.000168 ***
scale(NAcc_middle) -1.685e-01  1.570e-01  -1.073 0.306087    
scale(AIns_middle)  9.364e-02  1.372e-01   0.683 0.509000    
scale(MPFC_middle)  1.430e-01  1.338e-01   1.069 0.307996    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4204 on 11 degrees of freedom
Multiple R-squared:  0.8537,    Adjusted R-squared:  0.8005 
F-statistic: 16.04 on 4 and 11 DF,  p-value: 0.0001462

           R2m       R2c
[1,] 0.8105347 0.8105347
[1] 23.67864

FM_US_M22: Middle data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_middle) + scale(AIns_middle) + 
    scale(MPFC_middle), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.44224 -0.25199 -0.03754  0.31736  0.56953 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)                1.541e+01  3.394e-01  45.411 6.09e-12 ***
Theaters_US_M1             1.685e-04  3.387e-05   4.976 0.000764 ***
scale(Pos_arousal_scaled)  7.843e-02  1.393e-01   0.563 0.587220    
scale(Neg_arousal_scaled) -1.364e-01  1.393e-01  -0.979 0.353147    
scale(NAcc_middle)        -1.611e-01  1.572e-01  -1.025 0.332322    
scale(AIns_middle)         1.279e-01  1.829e-01   0.699 0.502230    
scale(MPFC_middle)         1.172e-01  1.466e-01   0.799 0.444654    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4199 on 9 degrees of freedom
Multiple R-squared:  0.8805,    Adjusted R-squared:  0.8008 
F-statistic: 11.05 on 6 and 9 DF,  p-value: 0.001026

           R2m       R2c
[1,] 0.8155404 0.8155404
[1] 24.43633

FM_US_M23: Offset data alone


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(NAcc_offset) + 
    scale(AIns_offset) + scale(MPFC_offset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.45430 -0.33861 -0.01704  0.20012  0.67277 

Coefficients:
                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)        15.0309917  0.3345914  44.923 8.13e-14 ***
Theaters_US_M1      0.0002087  0.0000331   6.305 5.80e-05 ***
scale(NAcc_offset)  0.0093962  0.1528761   0.061    0.952    
scale(AIns_offset)  0.0687571  0.1272437   0.540    0.600    
scale(MPFC_offset) -0.0271473  0.1510495  -0.180    0.861    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4457 on 11 degrees of freedom
Multiple R-squared:  0.8355,    Adjusted R-squared:  0.7757 
F-statistic: 13.96 on 4 and 11 DF,  p-value: 0.0002736

           R2m       R2c
[1,] 0.7883149 0.7883149
[1] 25.5531

FM_US_M24: Offset data + affective data + behavioral data


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_offset) + scale(AIns_offset) + 
    scale(MPFC_offset), data = AllSubs_NeuralActivation)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.5148 -0.2385 -0.1090  0.2637  0.5562 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)                1.516e+01  3.359e-01  45.117 6.46e-12 ***
Theaters_US_M1             1.956e-04  3.335e-05   5.865 0.000239 ***
scale(Pos_arousal_scaled)  1.061e-01  1.245e-01   0.852 0.416113    
scale(Neg_arousal_scaled) -1.534e-01  1.259e-01  -1.218 0.254159    
scale(NAcc_offset)        -2.488e-02  1.539e-01  -0.162 0.875134    
scale(AIns_offset)         1.245e-01  1.303e-01   0.956 0.364142    
scale(MPFC_offset)        -2.609e-02  1.520e-01  -0.172 0.867506    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4348 on 9 degrees of freedom
Multiple R-squared:  0.8719,    Adjusted R-squared:  0.7865 
F-statistic: 10.21 on 6 and 9 DF,  p-value: 0.00138

           R2m       R2c
[1,] 0.8033241 0.8033241
[1] 25.547

FM_US_M25: Seq data alone


Call:
lm(formula = log(Gross_US_M1) ~ +Theaters_US_M1 + scale(NAcc_onset) + 
    scale(AIns_middle) + scale(MPFC_offset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.44882 -0.31788 -0.04391  0.21377  0.62567 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)        1.524e+01  3.212e-01  47.436 4.48e-14 ***
Theaters_US_M1     1.871e-04  3.189e-05   5.866 0.000108 ***
scale(NAcc_onset)  1.630e-01  1.203e-01   1.355 0.202537    
scale(AIns_middle) 6.878e-02  1.147e-01   0.600 0.560913    
scale(MPFC_offset) 2.076e-02  1.265e-01   0.164 0.872627    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4149 on 11 degrees of freedom
Multiple R-squared:  0.8574,    Adjusted R-squared:  0.8056 
F-statistic: 16.54 on 4 and 11 DF,  p-value: 0.0001272

           R2m       R2c
[1,] 0.8151494 0.8151494
[1] 23.26338

FM_US_M26: Sqe data + affective data + behavioral data


Call:
lm(formula = log(Gross_Total_US) ~ +Total_Theaters_US + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_onset) + scale(AIns_middle) + 
    scale(MPFC_offset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.37432 -0.21825 -0.00611  0.20211  0.47060 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)                1.568e+01  2.315e-01  67.724 1.69e-13 ***
Total_Theaters_US          9.980e-05  1.411e-05   7.073 5.84e-05 ***
scale(Pos_arousal_scaled) -3.391e-01  1.313e-01  -2.583   0.0296 *  
scale(Neg_arousal_scaled)  9.721e-02  1.518e-01   0.640   0.5380    
scale(NAcc_onset)          3.500e-01  1.273e-01   2.749   0.0225 *  
scale(AIns_middle)         1.651e-01  1.268e-01   1.302   0.2252    
scale(MPFC_offset)         2.330e-01  1.569e-01   1.485   0.1717    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.351 on 9 degrees of freedom
Multiple R-squared:  0.9336,    Adjusted R-squared:  0.8893 
F-statistic: 21.09 on 6 and 9 DF,  p-value: 8.014e-05

           R2m       R2c
[1,] 0.8940089 0.8940089
[1] 18.70016

Total_US_M27: Seq data + affective data + behavioral data


Call:
lm(formula = log(Gross_Total_US) ~ +Total_Theaters_US + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + scale(NAcc_onset) + scale(AIns_middle) + 
    scale(MPFC_offset), data = AllSubs_NeuralActivation)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.37432 -0.21825 -0.00611  0.20211  0.47060 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)                1.568e+01  2.315e-01  67.724 1.69e-13 ***
Total_Theaters_US          9.980e-05  1.411e-05   7.073 5.84e-05 ***
scale(Pos_arousal_scaled) -3.391e-01  1.313e-01  -2.583   0.0296 *  
scale(Neg_arousal_scaled)  9.721e-02  1.518e-01   0.640   0.5380    
scale(NAcc_onset)          3.500e-01  1.273e-01   2.749   0.0225 *  
scale(AIns_middle)         1.651e-01  1.268e-01   1.302   0.2252    
scale(MPFC_offset)         2.330e-01  1.569e-01   1.485   0.1717    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.351 on 9 degrees of freedom
Multiple R-squared:  0.9336,    Adjusted R-squared:  0.8893 
F-statistic: 21.09 on 6 and 9 DF,  p-value: 8.014e-05

           R2m       R2c
[1,] 0.8940089 0.8940089
[1] 18.70016
---
title: "R Notebook"
output: html_notebook
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

# Load libraries
```{r}
library(knitr)
library(rmdformats)
library(ggplot2)
library(ggpubr)
library(GGally)
library(car)
```


```{r, warning = FALSE, message = FALSE}
library(tidyverse)
library(lme4)
library(lmerTest)
library("MuMIn")
library(lmtest)
library(boot)
```

Read dataset
```{r}
AllSubs_NeuralActivation <- read.csv('/Users/luisalvarez/Documents/GitHub/RM_Thesis_Neuroforecasting/ProcessedData/AllSubs_NeuralActivation_Aggregate_Combined_Comedy_clean.csv')
```
# Create data frames for each model.
```{r}
# Define aggregate variables. 
All_Gross_W1_log <- log(AllSubs_NeuralActivation$Gross_US_W1_num)
All_Theaters_W1 <- AllSubs_NeuralActivation$Theaters_US_W1_num

All_Gross_M1_log <- log(AllSubs_NeuralActivation$Gross_US_M1)
All_Theaters_M1 <- AllSubs_NeuralActivation$Theaters_US_M1

# Define affect variables.
All_PA <- AllSubs_NeuralActivation$Pos_arousal_scaled
All_NA <- AllSubs_NeuralActivation$Neg_arousal_scaled

FW_US_M1_df <- data.frame(All_Gross_W1_log, All_Theaters_W1) 
FM_US_M14_df <- data.frame(All_Gross_M1_log, All_Theaters_M1) 
```

```{r}
# Define ISC variables. 
All_NAcc_ISC <- AllSubs_NeuralActivation$NAcc_ISC
All_AIns_ISC <- AllSubs_NeuralActivation$AIns_ISC
All_MPFC_ISC <- AllSubs_NeuralActivation$MPFC_ISC

# Define models. 
FW_US_M2_df <- data.frame(All_NAcc_ISC, All_AIns_ISC, All_MPFC_ISC) 
FW_US_M3_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_ISC, All_AIns_ISC, All_MPFC_ISC) 
FM_US_M16_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_ISC, All_AIns_ISC, All_MPFC_ISC) 

```

```{r}
# Define whole variables. 
All_NAcc_whole <- AllSubs_NeuralActivation$NAcc_whole
All_AIns_whole <- AllSubs_NeuralActivation$AIns_whole
All_MPFC_whole <- AllSubs_NeuralActivation$MPFC_whole

# Define models. 
FW_US_M4_df <- data.frame(All_NAcc_whole, All_AIns_whole, All_MPFC_whole) 
FW_US_M5_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_whole, All_AIns_whole, All_MPFC_whole)
FM_US_M18_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_whole, All_AIns_whole, All_MPFC_whole)
```

```{r}
# Define onset variables. 
All_NAcc_onset <- AllSubs_NeuralActivation$NAcc_onset
All_AIns_onset <- AllSubs_NeuralActivation$AIns_onset
All_MPFC_onset <- AllSubs_NeuralActivation$MPFC_onset

# Define models. 
FW_US_M6_df <- data.frame(All_NAcc_onset, All_AIns_onset, All_MPFC_onset) 
FW_US_M7_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_onset, All_MPFC_onset)
FM_US_M20_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_onset, All_MPFC_onset)
```

```{r}
# Define middle variables. 
All_NAcc_middle <- AllSubs_NeuralActivation$NAcc_middle
All_AIns_middle <- AllSubs_NeuralActivation$AIns_middle
All_MPFC_middle <- AllSubs_NeuralActivation$MPFC_middle

# Define models. 
FW_US_M8_df <- data.frame(All_NAcc_middle, All_AIns_middle, All_MPFC_middle) 
FW_US_M9_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_middle, All_AIns_middle, All_MPFC_middle) 
FM_US_M22_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_middle, All_AIns_middle, All_MPFC_middle)
```

```{r}
# Define offset variables. 
All_NAcc_offset <- AllSubs_NeuralActivation$NAcc_offset
All_AIns_offset <- AllSubs_NeuralActivation$AIns_offset
All_MPFC_offset <- AllSubs_NeuralActivation$MPFC_offset

# Define models. 
FW_US_M10_df <- data.frame(All_NAcc_offset, All_AIns_offset, All_MPFC_offset) 
FW_US_M11_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_offset, All_AIns_offset, All_MPFC_offset)
FM_US_M24_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_offset, All_AIns_offset, All_MPFC_offset)

# Seq models. 
FW_US_M12_df <- data.frame(All_NAcc_onset, All_AIns_middle, All_MPFC_offset) 
FW_US_M13_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_middle, All_MPFC_offset)
FM_US_M26_df <- data.frame(All_Gross_M1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_middle, All_MPFC_offset)
```


# Neuroforecasting: First Week US.
## M1: Behavioral data + Affective data
```{r, echo = FALSE}
FW_US_M1 <- lm(log(Gross_US_W1_num) ~ Theaters_US_W1_num
         + scale(Pos_arousal_scaled) 
         + scale(Neg_arousal_scaled)
            , data = AllSubs_NeuralActivation )
summary(FW_US_M1)
r.squaredGLMM(FW_US_M1)
AIC(FW_US_M1)
ggpairs(FW_US_M1_df)
```

# FW_US_M2: ISC data alone
```{r, echo = FALSE}
FW_US_M2 <- lm(log(Gross_US_W1_num) ~  
              + Theaters_US_W1_num 
              + scale(NAcc_ISC) 
              + scale(AIns_ISC) 
              + scale(MPFC_ISC) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M2)
r.squaredGLMM(FW_US_M2)
AIC(FW_US_M2)
ggpairs(FW_US_M2_df)
```
# FW_US_M3: ISC data + affective data + behavioral data
```{r, echo = FALSE}
FW_US_M3 <- lm(log(Gross_US_W1_num) ~  
             + Theaters_US_W1_num 
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_ISC) # For some reason NAcc is correlated with AIns 
             + scale(AIns_ISC) # When removing AIns, NAcc becomes sig.
             + scale(MPFC_ISC) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M3)
r.squaredGLMM(FW_US_M3)
AIC(FW_US_M3)
ggpairs(FW_US_M3_df)
```
# FW_US_M4: Whole data alone
```{r, echo = FALSE}
FW_US_M4 <- lm(log(Gross_US_W1_num) ~  
              + Theaters_US_W1_num 
              + scale(NAcc_whole) 
              + scale(AIns_whole) 
              + scale(MPFC_whole) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M4)
r.squaredGLMM(FW_US_M4)
AIC(FW_US_M4)
ggpairs(FW_US_M4_df)
```

# FW_US_M5: Whole data + affective data + behavioral data
```{r, echo = FALSE}
FW_US_M5 <- lm(log(Gross_US_W1_num) ~  
             + Theaters_US_W1_num 
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_whole) 
             + scale(AIns_whole) 
             + scale(MPFC_whole) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M5)
r.squaredGLMM(FW_US_M5)
AIC(FW_US_M5)
ggpairs(FW_US_M5_df)
```

# FW_US_M6: Onset data alone
```{r, echo = FALSE}
FW_US_M6 <- lm(log(Gross_US_W1_num) ~  
              + Theaters_US_W1_num 
              + scale(NAcc_onset) 
              + scale(AIns_onset) 
              + scale(MPFC_onset) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M6)
r.squaredGLMM(FW_US_M6)
AIC(FW_US_M6)
ggpairs(FW_US_M6_df)
```

# FW_US_M7: Onset data + affective data + behavioral data
```{r, echo = FALSE}
FW_US_M7 <- lm(log(Gross_US_W1_num) ~  
             + Theaters_US_W1_num 
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_onset) 
             + scale(AIns_onset) 
             + scale(MPFC_onset) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M7)
r.squaredGLMM(FW_US_M7)
AIC(FW_US_M7)
ggpairs(FW_US_M7_df)
```

# FW_US_M8: Middle data alone
```{r, echo = FALSE}
FW_US_M8 <- lm(log(Gross_US_W1_num) ~  
              + Theaters_US_W1_num 
              + scale(NAcc_middle) 
              + scale(AIns_middle) 
              + scale(MPFC_middle) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M8)
r.squaredGLMM(FW_US_M8)
AIC(FW_US_M8)
ggpairs(FW_US_M8_df)
```

# FW_US_M9: Middle data + affective data + behavioral data
```{r, echo = FALSE}
FW_US_M9 <- lm(log(Gross_US_W1_num) ~  
             + Theaters_US_W1_num 
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_middle) 
             + scale(AIns_middle) 
             + scale(MPFC_middle) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M9)
r.squaredGLMM(FW_US_M9)
AIC(FW_US_M9)
ggpairs(FW_US_M9_df)
```

# FW_US_M10: Offset data alone
```{r, echo = FALSE}
FW_US_M10 <- lm(log(Gross_US_W1_num) ~  
              + Theaters_US_W1_num 
              + scale(NAcc_offset) 
              + scale(AIns_offset) 
              + scale(MPFC_offset) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M10)
r.squaredGLMM(FW_US_M10)
AIC(FW_US_M10)
ggpairs(FW_US_M10_df)
```

# FW_US_M11: Onset data + affective data + behavioral data
```{r, echo = FALSE}
FW_US_M11 <- lm(log(Gross_US_W1_num) ~  
             + Theaters_US_W1_num 
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_offset) 
             + scale(AIns_offset) 
             + scale(MPFC_offset) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M11)
r.squaredGLMM(FW_US_M11)
AIC(FW_US_M11)
ggpairs(FW_US_M11_df)
```

# FW_US_M12: Seq data alone
```{r, echo = FALSE}
FW_US_M12 <- lm(log(Gross_US_W1_num) ~  
              + Theaters_US_W1_num 
              + scale(NAcc_onset) 
              + scale(AIns_middle) 
              + scale(MPFC_offset) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M12)
r.squaredGLMM(FW_US_M12)
AIC(FW_US_M12)
ggpairs(FW_US_M12_df)
```

# FW_US_M13: Seq data + affective data + behavioral data
```{r, echo = FALSE}
FW_US_M13 <- lm(log(Gross_US_W1_num) ~  
             + Theaters_US_W1_num 
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_onset) 
             + scale(AIns_middle) 
             + scale(MPFC_offset) 
            , data = AllSubs_NeuralActivation)
summary(FW_US_M13)
r.squaredGLMM(FW_US_M13)
AIC(FW_US_M13)
ggpairs(FW_US_M13_df)
```
# Neuroforecasting: First Month US.

## FM_US_M14: Behavioral data + affective data
```{r, echo = FALSE}
FM_US_M14 <- lm(log(Gross_US_M1) ~  
         + Theaters_US_M1 
         + scale(Pos_arousal_scaled) 
         + scale(Neg_arousal_scaled)
         #+ scale(W_score_scaled)
            , data = AllSubs_NeuralActivation )
summary(FM_US_M14)
r.squaredGLMM(FM_US_M14)
AIC(FM_US_M14)
ggpairs(FM_US_M14_df)
```

# FM_US_M15: ISC data alone
```{r, echo = FALSE}
FM_US_M15 <- lm(log(Gross_US_M1) ~  
              + Theaters_US_M1
              + scale(NAcc_ISC) 
              + scale(AIns_ISC) 
              + scale(MPFC_ISC) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M15)
r.squaredGLMM(FM_US_M15)
AIC(FM_US_M15)
```

# FM_US_M16: ISC data + affective data + behavioral data
```{r, echo = FALSE}
FM_US_M16 <- lm(log(Gross_US_M1) ~  
             + Theaters_US_M1
             #+ Total_weeks 
             #+ Weeks_avg_per_theater
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_ISC) 
             + scale(AIns_ISC) 
             + scale(MPFC_ISC) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M16)
r.squaredGLMM(FM_US_M16)
AIC(FM_US_M16)
ggpairs(FM_US_M16_df)
```
# FM_US_M17: Whole data alone
```{r, echo = FALSE}
FM_US_M17 <- lm(log(Gross_US_M1) ~  
              + Theaters_US_M1
              + scale(NAcc_whole) 
              + scale(AIns_whole) 
              + scale(MPFC_whole) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M17)
r.squaredGLMM(FM_US_M17)
AIC(FM_US_M17)
```

# FM_US_M18: Whole data + affective data + behavioral data
```{r, echo = FALSE}
FM_US_M18 <- lm(log(Gross_US_M1) ~  
             + Theaters_US_M1
             #+ Total_weeks 
             #+ Weeks_avg_per_theater
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_whole) 
             + scale(AIns_whole) 
             + scale(MPFC_whole) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M18)
r.squaredGLMM(FM_US_M18)
AIC(FM_US_M18)
ggpairs(FM_US_M18_df)
```

# FM_US_M19: Onset data alone
```{r, echo = FALSE}
FM_US_M19 <- lm(log(Gross_US_M1) ~  
              + Theaters_US_M1
              + scale(NAcc_onset) 
              + scale(AIns_onset) 
              + scale(MPFC_onset) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M19)
r.squaredGLMM(FM_US_M19)
AIC(FM_US_M19)
```

# FM_US_M20: Onset data + affective data + behavioral data
```{r, echo = FALSE}
FM_US_M20 <- lm(log(Gross_US_M1) ~  
             + Theaters_US_M1
             #+ Total_weeks 
             #+ Weeks_avg_per_theater
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_onset) 
             + scale(AIns_onset) 
             + scale(MPFC_onset) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M20)
r.squaredGLMM(FM_US_M20)
AIC(FM_US_M20)
ggpairs(FM_US_M20_df)
```

# FM_US_M17: Middle data alone
```{r, echo = FALSE}
FM_US_M21 <- lm(log(Gross_US_M1) ~  
              + Theaters_US_M1
              + scale(NAcc_middle) 
              + scale(AIns_middle) 
              + scale(MPFC_middle) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M21)
r.squaredGLMM(FM_US_M21)
AIC(FM_US_M21)
```

# FM_US_M22: Middle data + affective data + behavioral data
```{r, echo = FALSE}
FM_US_M22 <- lm(log(Gross_US_M1) ~  
             + Theaters_US_M1
             #+ Total_weeks 
             #+ Weeks_avg_per_theater
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_middle) 
             + scale(AIns_middle) 
             + scale(MPFC_middle) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M22)
r.squaredGLMM(FM_US_M22)
AIC(FM_US_M22)
ggpairs(FM_US_M22_df)
```

# FM_US_M23: Offset data alone
```{r, echo = FALSE}
FM_US_M23 <- lm(log(Gross_US_M1) ~  
              + Theaters_US_M1
              + scale(NAcc_offset) 
              + scale(AIns_offset) 
              + scale(MPFC_offset) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M23)
r.squaredGLMM(FM_US_M23)
AIC(FM_US_M23)
```

# FM_US_M24: Offset data + affective data + behavioral data
```{r, echo = FALSE}
FM_US_M24 <- lm(log(Gross_US_M1) ~  
             + Theaters_US_M1
             #+ Total_weeks 
             #+ Weeks_avg_per_theater
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_offset) 
             + scale(AIns_offset) 
             + scale(MPFC_offset) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M24)
r.squaredGLMM(FM_US_M24)
AIC(FM_US_M24)
ggpairs(FM_US_M24_df)
```

# FM_US_M25: Seq data alone
```{r, echo = FALSE}
FM_US_M25 <- lm(log(Gross_US_M1) ~  
              + Theaters_US_M1
              + scale(NAcc_onset) 
              + scale(AIns_middle) 
              + scale(MPFC_offset) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M25)
r.squaredGLMM(FM_US_M25)
AIC(FM_US_M25)
```

# FM_US_M26: Sqe data + affective data + behavioral data
```{r, echo = FALSE}
FM_US_M26 <- lm(log(Gross_US_M1) ~  
             + Theaters_US_M1 
             #+ Total_weeks 
             #+ Weeks_avg_per_theater
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_onset) 
             + scale(AIns_middle) 
             + scale(MPFC_offset) 
            , data = AllSubs_NeuralActivation)
summary(FM_US_M26)
r.squaredGLMM(FM_US_M26)
AIC(FM_US_M26)
ggpairs(FM_US_M26_df)
```
# Total_US_M27: Seq data + affective data + behavioral data
```{r, echo = FALSE}
Total_US_M27 <- lm(log(Gross_Total_US) ~  
             + Total_Theaters_US 
             #+ Total_weeks 
             #+ Weeks_avg_per_theater
             + scale(Pos_arousal_scaled) 
             + scale(Neg_arousal_scaled)  
             #+ scale(W_score_scaled) 
             + scale(NAcc_onset) 
             + scale(AIns_middle) 
             + scale(MPFC_offset) 
            , data = AllSubs_NeuralActivation)
summary(Total_US_M27)
r.squaredGLMM(Total_US_M27)
AIC(Total_US_M27)

```




